Comparison of sixteen methods for fusion of data from impulse-radar sensors and depth sensors applied for monitoring of elderly persons
•Data fusion in non-intrusive system for monitoring of elderly persons is addressed.•Two monitoring techniques are considered: impulse-radar sensors and depth sensors.•Sixteen methods of data fusion are systematically compared using real-world data.•Conclusions of practical nature are formulated. Th...
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Veröffentlicht in: | Measurement : journal of the International Measurement Confederation 2020-03, Vol.154, p.107455, Article 107455 |
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container_title | Measurement : journal of the International Measurement Confederation |
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creator | Mazurek, Paweł Wagner, Jakub Miękina, Andrzej Morawski, Roman Z. |
description | •Data fusion in non-intrusive system for monitoring of elderly persons is addressed.•Two monitoring techniques are considered: impulse-radar sensors and depth sensors.•Sixteen methods of data fusion are systematically compared using real-world data.•Conclusions of practical nature are formulated.
This paper is devoted to the comparison of sixteen methods for fusion of measurement data from impulse-radar sensors and infrared depth sensors, i.e. two sensor technologies that may be employed in care services for elderly persons. These methods are compared with respect to their potential for decreasing the uncertainty of estimation of monitored person’s position: eight of them consist in fusing the impulse-radar data and depth data whenever new data points are available, and the other eight consist in fusing the whole sequences of the data acquired during a predefined time interval. The numerical experiments, based on the real-world data, show that the best overall results are obtained for two methods of data fusion, viz. a method based on the Kalman filter and a method using the Tikhonov regularization technique to generate a smooth approximation of the data. |
doi_str_mv | 10.1016/j.measurement.2019.107455 |
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This paper is devoted to the comparison of sixteen methods for fusion of measurement data from impulse-radar sensors and infrared depth sensors, i.e. two sensor technologies that may be employed in care services for elderly persons. These methods are compared with respect to their potential for decreasing the uncertainty of estimation of monitored person’s position: eight of them consist in fusing the impulse-radar data and depth data whenever new data points are available, and the other eight consist in fusing the whole sequences of the data acquired during a predefined time interval. The numerical experiments, based on the real-world data, show that the best overall results are obtained for two methods of data fusion, viz. a method based on the Kalman filter and a method using the Tikhonov regularization technique to generate a smooth approximation of the data.</description><identifier>ISSN: 0263-2241</identifier><identifier>EISSN: 1873-412X</identifier><identifier>DOI: 10.1016/j.measurement.2019.107455</identifier><language>eng</language><publisher>London: Elsevier Ltd</publisher><subject>Data acquisition ; Data integration ; Data points ; Depth sensor ; Elder care ; Healthcare ; Impulse-radar sensor ; Infrared detectors ; Infrared radar ; Kalman filters ; Measurement data fusion ; Measurement methods ; Older people ; Radar data ; Radar systems ; Regularization ; Sensors</subject><ispartof>Measurement : journal of the International Measurement Confederation, 2020-03, Vol.154, p.107455, Article 107455</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. Mar 15, 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c349t-f7277e78eae5ee46893436794b03e1ead952af8f9e4e440846b8e5476769bf313</citedby><cites>FETCH-LOGICAL-c349t-f7277e78eae5ee46893436794b03e1ead952af8f9e4e440846b8e5476769bf313</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.measurement.2019.107455$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Mazurek, Paweł</creatorcontrib><creatorcontrib>Wagner, Jakub</creatorcontrib><creatorcontrib>Miękina, Andrzej</creatorcontrib><creatorcontrib>Morawski, Roman Z.</creatorcontrib><title>Comparison of sixteen methods for fusion of data from impulse-radar sensors and depth sensors applied for monitoring of elderly persons</title><title>Measurement : journal of the International Measurement Confederation</title><description>•Data fusion in non-intrusive system for monitoring of elderly persons is addressed.•Two monitoring techniques are considered: impulse-radar sensors and depth sensors.•Sixteen methods of data fusion are systematically compared using real-world data.•Conclusions of practical nature are formulated.
This paper is devoted to the comparison of sixteen methods for fusion of measurement data from impulse-radar sensors and infrared depth sensors, i.e. two sensor technologies that may be employed in care services for elderly persons. These methods are compared with respect to their potential for decreasing the uncertainty of estimation of monitored person’s position: eight of them consist in fusing the impulse-radar data and depth data whenever new data points are available, and the other eight consist in fusing the whole sequences of the data acquired during a predefined time interval. The numerical experiments, based on the real-world data, show that the best overall results are obtained for two methods of data fusion, viz. a method based on the Kalman filter and a method using the Tikhonov regularization technique to generate a smooth approximation of the data.</description><subject>Data acquisition</subject><subject>Data integration</subject><subject>Data points</subject><subject>Depth sensor</subject><subject>Elder care</subject><subject>Healthcare</subject><subject>Impulse-radar sensor</subject><subject>Infrared detectors</subject><subject>Infrared radar</subject><subject>Kalman filters</subject><subject>Measurement data fusion</subject><subject>Measurement methods</subject><subject>Older people</subject><subject>Radar data</subject><subject>Radar systems</subject><subject>Regularization</subject><subject>Sensors</subject><issn>0263-2241</issn><issn>1873-412X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqNkE-LFDEQxYO44Ljud4h47jH_OukcZVBXWPCi4C1kOhU3w3TSVtLifgK_tj32wnr0VPCq3u9Rj5DXnO054_rtaT-BrwvCBLntBeN21Y3q-2dkxwcjO8XFt-dkx4SWnRCKvyAvaz0xxrS0ekd-H8o0e0y1ZFoirelXA8h0gnZfQqWxII1LTds2-OZpxDLRNM3LuUKHPnikFXItWKnPgQaY2_2TMs_nBOEvZyo5tYIpf7-w4BwAzw90Blyz6ytyFf1KvHmc1-Trh_dfDrfd3eePnw7v7rpRKtu6aIQxYAbw0AMoPVippDZWHZkEDj7YXvg4RAsKlGKD0scBemW00fYYJZfX5M3GnbH8WKA2dyoL5jXSCSXFMPRWm_XKblcjlloRopsxTR4fHGfu0rs7uX96d5fe3db76j1sXljf-JkAXR0T5BFCQhibCyX9B-UPwROVHA</recordid><startdate>20200315</startdate><enddate>20200315</enddate><creator>Mazurek, Paweł</creator><creator>Wagner, Jakub</creator><creator>Miękina, Andrzej</creator><creator>Morawski, Roman Z.</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20200315</creationdate><title>Comparison of sixteen methods for fusion of data from impulse-radar sensors and depth sensors applied for monitoring of elderly persons</title><author>Mazurek, Paweł ; Wagner, Jakub ; Miękina, Andrzej ; Morawski, Roman Z.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c349t-f7277e78eae5ee46893436794b03e1ead952af8f9e4e440846b8e5476769bf313</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Data acquisition</topic><topic>Data integration</topic><topic>Data points</topic><topic>Depth sensor</topic><topic>Elder care</topic><topic>Healthcare</topic><topic>Impulse-radar sensor</topic><topic>Infrared detectors</topic><topic>Infrared radar</topic><topic>Kalman filters</topic><topic>Measurement data fusion</topic><topic>Measurement methods</topic><topic>Older people</topic><topic>Radar data</topic><topic>Radar systems</topic><topic>Regularization</topic><topic>Sensors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mazurek, Paweł</creatorcontrib><creatorcontrib>Wagner, Jakub</creatorcontrib><creatorcontrib>Miękina, Andrzej</creatorcontrib><creatorcontrib>Morawski, Roman Z.</creatorcontrib><collection>CrossRef</collection><jtitle>Measurement : journal of the International Measurement Confederation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mazurek, Paweł</au><au>Wagner, Jakub</au><au>Miękina, Andrzej</au><au>Morawski, Roman Z.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of sixteen methods for fusion of data from impulse-radar sensors and depth sensors applied for monitoring of elderly persons</atitle><jtitle>Measurement : journal of the International Measurement Confederation</jtitle><date>2020-03-15</date><risdate>2020</risdate><volume>154</volume><spage>107455</spage><pages>107455-</pages><artnum>107455</artnum><issn>0263-2241</issn><eissn>1873-412X</eissn><abstract>•Data fusion in non-intrusive system for monitoring of elderly persons is addressed.•Two monitoring techniques are considered: impulse-radar sensors and depth sensors.•Sixteen methods of data fusion are systematically compared using real-world data.•Conclusions of practical nature are formulated.
This paper is devoted to the comparison of sixteen methods for fusion of measurement data from impulse-radar sensors and infrared depth sensors, i.e. two sensor technologies that may be employed in care services for elderly persons. These methods are compared with respect to their potential for decreasing the uncertainty of estimation of monitored person’s position: eight of them consist in fusing the impulse-radar data and depth data whenever new data points are available, and the other eight consist in fusing the whole sequences of the data acquired during a predefined time interval. The numerical experiments, based on the real-world data, show that the best overall results are obtained for two methods of data fusion, viz. a method based on the Kalman filter and a method using the Tikhonov regularization technique to generate a smooth approximation of the data.</abstract><cop>London</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.measurement.2019.107455</doi></addata></record> |
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subjects | Data acquisition Data integration Data points Depth sensor Elder care Healthcare Impulse-radar sensor Infrared detectors Infrared radar Kalman filters Measurement data fusion Measurement methods Older people Radar data Radar systems Regularization Sensors |
title | Comparison of sixteen methods for fusion of data from impulse-radar sensors and depth sensors applied for monitoring of elderly persons |
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